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+<a href="_workload_utils_8hpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;</div><div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="preprocessor">#pragma once</span></div><div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;</div><div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_cpu_tensor_handle_8hpp.xhtml">CpuTensorHandle.hpp</a>&quot;</span></div><div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;</div><div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="include_2armnn_2backends_2_i_tensor_handle_8hpp.xhtml">armnn/backends/ITensorHandle.hpp</a>&gt;</span></div><div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;</div><div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_tensor_8hpp.xhtml">armnn/Tensor.hpp</a>&gt;</span></div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;</div><div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_permute_8hpp.xhtml">armnnUtils/Permute.hpp</a>&gt;</span></div><div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;</div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_half_8hpp.xhtml">Half.hpp</a>&gt;</span></div><div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_profiling_8hpp.xhtml">Profiling.hpp</a>&gt;</span></div><div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;</div><div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;<span class="preprocessor">#include &lt;boost/cast.hpp&gt;</span></div><div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;</div><div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></div><div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;{</div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;<span class="keyword">namespace</span></div><div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;{</div><div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;</div><div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> ArrayType, <span class="keyword">typename</span> Arg&gt;</div><div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;<span class="keywordtype">void</span> AssignValues(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> num, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>&amp; idx, <span class="keyword">const</span> ArrayType&amp; array, Arg&amp; arg)</div><div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;{</div><div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;    <span class="keywordflow">if</span> (idx &gt;= num)</div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;    {</div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;        <span class="keywordflow">return</span>;</div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;    }</div><div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;</div><div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;    arg = array[(num - 1) - idx];</div><div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;    idx++;</div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;}</div><div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;</div><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keyword">typename</span> ArrayType, <span class="keyword">typename</span>... Args&gt;</div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;<span class="keywordtype">void</span> AssignValues(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> num, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> idx, <span class="keyword">const</span> ArrayType&amp; array, T&amp; assignee, Args&amp;... args)</div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;{</div><div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;    AssignValues(num, idx, array, assignee);</div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;</div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;    AssignValues(num, idx, array, args...);</div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;}</div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;</div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;}    <span class="comment">// anonymous namespace</span></div><div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;</div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> CopyFunc&gt;</div><div class="line"><a name="l00049"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a92c91193007aa49f4732d6dba5397f8d">   49</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="namespacearmnn.xhtml#a92c91193007aa49f4732d6dba5397f8d">CopyTensorContentsGeneric</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml">ITensorHandle</a>* srcTensor, <a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml">ITensorHandle</a>* dstTensor, CopyFunc copy)</div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;{</div><div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;    <span class="comment">// For ease of understanding, names are assigned to the dimensions</span></div><div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;    <span class="comment">// of the tensor as if NHWC, however this routine works with any 5D tensor</span></div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;    static_assert(<a class="code" href="namespacearmnn.xhtml#abdcd184ed3bd648bb31d385040cafd5d">MaxNumOfTensorDimensions</a> == 5, <span class="stringliteral">&quot;Please update CopyTensorContents&quot;</span>);</div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;</div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> srcStrides      = srcTensor-&gt;<a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml#a30c3e09ce55369b66469443a4ca5ef03">GetStrides</a>();</div><div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>&amp; srcShape = srcTensor-&gt;<a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml#affd5aae75cad90f472f96cfd25a13f29">GetShape</a>();</div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;    <span class="keyword">const</span> <span class="keyword">auto</span> srcSize          = srcTensor-&gt;<a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml#a30c3e09ce55369b66469443a4ca5ef03">GetStrides</a>()[0] * srcShape[0];</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;    <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(srcSize);  <span class="comment">// Only used for asserts</span></div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> dstStrides      = dstTensor-&gt;<a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml#a30c3e09ce55369b66469443a4ca5ef03">GetStrides</a>();</div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>&amp; dstShape = dstTensor-&gt;<a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml#affd5aae75cad90f472f96cfd25a13f29">GetShape</a>();</div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;    <span class="keyword">const</span> <span class="keyword">auto</span> dstSize          = dstTensor-&gt;<a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml#a30c3e09ce55369b66469443a4ca5ef03">GetStrides</a>()[0] * dstShape[0];</div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;    <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(dstSize);  <span class="comment">// Only used for asserts</span></div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;</div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;    <span class="keywordtype">size_t</span> srcDepth    = 1;</div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;    <span class="keywordtype">size_t</span> srcBatches  = 1;</div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;    <span class="keywordtype">size_t</span> srcHeight   = 1;</div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;    <span class="keywordtype">size_t</span> srcWidth    = 1;</div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;    <span class="keywordtype">size_t</span> srcChannels = 1;</div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;    AssignValues(srcShape.<a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>(),</div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;                 0,</div><div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;                 srcShape,</div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;                 srcChannels,</div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;                 srcWidth,</div><div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;                 srcHeight,</div><div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;                 srcBatches,</div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;                 srcDepth);</div><div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;</div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;    <span class="keywordtype">size_t</span> srcDepthStride   = 0;</div><div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;    <span class="keywordtype">size_t</span> srcBatchStride   = 0;</div><div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;    <span class="keywordtype">size_t</span> srcHeightStride  = 0;</div><div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;    <span class="keywordtype">size_t</span> srcWidthStride   = 0;</div><div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;    <span class="keywordtype">size_t</span> srcChannelStride = 0;</div><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;    AssignValues(srcStrides.<a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>(),</div><div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;                 0,</div><div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;                 srcStrides,</div><div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;                 srcChannelStride,</div><div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;                 srcWidthStride,</div><div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;                 srcHeightStride,</div><div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;                 srcBatchStride,</div><div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;                 srcDepthStride);</div><div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;</div><div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;    <span class="keywordtype">size_t</span> dstDepth    = 1;</div><div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;    <span class="keywordtype">size_t</span> dstBatches  = 1;</div><div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;    <span class="keywordtype">size_t</span> dstHeight   = 1;</div><div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;    <span class="keywordtype">size_t</span> dstWidth    = 1;</div><div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;    <span class="keywordtype">size_t</span> dstChannels = 1;</div><div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;    AssignValues(dstShape.<a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>(),</div><div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;                 0,</div><div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;                 dstShape,</div><div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;                 dstChannels,</div><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;                 dstWidth,</div><div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;                 dstHeight,</div><div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;                 dstBatches,</div><div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;                 dstDepth);</div><div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;</div><div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;    <span class="keywordtype">size_t</span> dstDepthStride   = 0;</div><div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;    <span class="keywordtype">size_t</span> dstBatchStride   = 0;</div><div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;    <span class="keywordtype">size_t</span> dstHeightStride  = 0;</div><div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;    <span class="keywordtype">size_t</span> dstWidthStride   = 0;</div><div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;    <span class="keywordtype">size_t</span> dstChannelStride = 0;</div><div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;    AssignValues(dstStrides.<a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>(),</div><div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;                 0,</div><div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;                 dstStrides,</div><div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;                 dstChannelStride,</div><div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;                 dstWidthStride,</div><div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;                 dstHeightStride,</div><div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;                 dstBatchStride,</div><div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;                 dstDepthStride);</div><div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;</div><div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">char</span>* srcDataStart;</div><div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">char</span>* dstDataStart;</div><div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;    {</div><div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;        <a class="code" href="_profiling_8hpp.xhtml#a5ccc65e2c464ac05ce311fdae7ede03a">ARMNN_SCOPED_PROFILING_EVENT</a>(<a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">Compute::Undefined</a>, <span class="stringliteral">&quot;Synchronize buffers&quot;</span>);</div><div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;        srcDataStart = <span class="keyword">static_cast&lt;</span><span class="keyword">const </span>uint8_t*<span class="keyword">&gt;</span>(srcTensor-&gt;<a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml#a9afbc055a017adf1bc38ee137bca6e90">Map</a>());</div><div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;        dstDataStart = <span class="keyword">static_cast&lt;</span>uint8_t*<span class="keyword">&gt;</span>(dstTensor-&gt;<a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml#a9afbc055a017adf1bc38ee137bca6e90">Map</a>());</div><div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;    }</div><div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;</div><div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;    <span class="keywordtype">size_t</span> copyLength  = std::min(srcChannels * srcChannelStride, dstChannels * dstChannelStride);</div><div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;    <span class="keywordtype">size_t</span> copyWidth   = std::min(srcWidth, dstWidth);</div><div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;    <span class="keywordtype">size_t</span> copyHeight  = std::min(srcHeight, dstHeight);</div><div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;    <span class="keywordtype">size_t</span> copyBatches = std::min(srcBatches, dstBatches);</div><div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;    <span class="keywordtype">size_t</span> copyDepth   = std::min(srcDepth, dstDepth);</div><div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;</div><div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;    <span class="comment">// Coalesce inner dimensions where possible</span></div><div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;    <span class="comment">// to reduce overheard calling copy() and to</span></div><div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;    <span class="comment">// allow for memory bandwidth optimisations</span></div><div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;    <span class="keywordflow">if</span> (copyLength == srcWidthStride &amp;&amp;</div><div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;        copyLength == dstWidthStride)</div><div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;    {</div><div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;        <span class="comment">// There is no special padding between rows,</span></div><div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;        <span class="comment">// and sizes are compatible, so copy whole rows</span></div><div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;        copyLength *= copyWidth;</div><div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;        copyWidth = 1;</div><div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;</div><div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;        <span class="keywordflow">if</span> (copyLength == srcHeightStride &amp;&amp;</div><div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;            copyLength == dstHeightStride)</div><div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;        {</div><div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;            <span class="comment">// There is no special padding between batches</span></div><div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;            <span class="comment">// and sizes are compatible so copy whole batches</span></div><div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;            copyLength *= copyHeight;</div><div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;            copyHeight = 1;</div><div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;        }</div><div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;    }</div><div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;</div><div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">char</span>* srcData = srcDataStart;</div><div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">char</span>* dstData = dstDataStart;</div><div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> d = 0; d &lt; copyDepth; ++d)</div><div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;    {</div><div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;        <span class="keyword">auto</span> srcPtrDepth = srcData;</div><div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;        <span class="keyword">auto</span> dstPtrDepth = dstData;</div><div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> b = 0; b &lt; copyBatches; ++b)</div><div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;        {</div><div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;            <span class="keyword">auto</span> srcPtrBatch = srcData;</div><div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;            <span class="keyword">auto</span> dstPtrBatch = dstData;</div><div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;            <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> h = 0; h &lt; copyHeight; ++h)</div><div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;            {</div><div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;                <span class="keyword">auto</span> srcPtrChannel = srcData;</div><div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;                <span class="keyword">auto</span> dstPtrChannel = dstData;</div><div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;                <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> w = 0; w &lt; copyWidth; ++w)</div><div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;                {</div><div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;                    BOOST_ASSERT(srcData &gt;= srcDataStart &amp;&amp; srcData + copyLength &lt;= srcDataStart + srcSize);</div><div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;                    BOOST_ASSERT(dstData &gt;= dstDataStart &amp;&amp; dstData + copyLength &lt;= dstDataStart + dstSize);</div><div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;                    copy(dstData, srcData, copyLength);</div><div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;                    dstData += dstWidthStride;</div><div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;                    srcData += srcWidthStride;</div><div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;                }</div><div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;                dstData += (<span class="keyword">static_cast&lt;</span><span class="keywordtype">long</span><span class="keyword">&gt;</span>(dstHeightStride) - (dstData - dstPtrChannel));</div><div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;                srcData += (<span class="keyword">static_cast&lt;</span><span class="keywordtype">long</span><span class="keyword">&gt;</span>(srcHeightStride) - (srcData - srcPtrChannel));</div><div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;            }</div><div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;            dstData += (<span class="keyword">static_cast&lt;</span><span class="keywordtype">long</span><span class="keyword">&gt;</span>(dstBatchStride) - (dstData - dstPtrBatch));</div><div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;            srcData += (<span class="keyword">static_cast&lt;</span><span class="keywordtype">long</span><span class="keyword">&gt;</span>(srcBatchStride) - (srcData - srcPtrBatch));</div><div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;        }</div><div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;        dstData += (<span class="keyword">static_cast&lt;</span><span class="keywordtype">long</span><span class="keyword">&gt;</span>(dstDepthStride) - (dstData - dstPtrDepth));</div><div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;        srcData += (<span class="keyword">static_cast&lt;</span><span class="keywordtype">long</span><span class="keyword">&gt;</span>(srcDepthStride) - (srcData - srcPtrDepth));</div><div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;    }</div><div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;</div><div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;    srcTensor-&gt;<a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml#a563609828050f1b3a7868c23f3365923">Unmap</a>();</div><div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;    dstTensor-&gt;<a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml#a563609828050f1b3a7868c23f3365923">Unmap</a>();</div><div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;}</div><div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;</div><div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> SrcTensorHandleType, <span class="keyword">typename</span> DstTensorHandleType, <span class="keyword">typename</span> DescriptorType&gt;</div><div class="line"><a name="l00192"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#afb5b53a8b0c01d4f27830bef0f25ca09">  192</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="namespacearmnn.xhtml#afb5b53a8b0c01d4f27830bef0f25ca09">GatherTensorHandlePairs</a>(<span class="keyword">const</span> DescriptorType&amp; descriptor,</div><div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;                             std::vector&lt;std::pair&lt;SrcTensorHandleType*, DstTensorHandleType*&gt;&gt;&amp; tensorHandlePairs)</div><div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;{</div><div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numInputs = <span class="keyword">static_cast&lt;</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">&gt;</span>(descriptor.m_Inputs.size());</div><div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;    tensorHandlePairs.reserve(numInputs);</div><div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;</div><div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; numInputs; ++i)</div><div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;    {</div><div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;        SrcTensorHandleType* <span class="keyword">const</span> srcTensorHandle =</div><div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;            boost::polymorphic_downcast&lt;SrcTensorHandleType*&gt;(descriptor.m_Inputs[i]);</div><div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;        DstTensorHandleType* <span class="keyword">const</span> dstTensorHandle =</div><div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;            boost::polymorphic_downcast&lt;DstTensorHandleType*&gt;(descriptor.m_Outputs[i]);</div><div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;</div><div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;        tensorHandlePairs.emplace_back(srcTensorHandle, dstTensorHandle);</div><div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;    }</div><div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;}</div><div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;</div><div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;int32_t <a class="code" href="namespacearmnn.xhtml#ad69ffa576a596b9eb20ab6a41420c541">ConvertMaskToACLFormat</a>(int32_t mask, int32_t numDim);</div><div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;</div><div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;<a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> <a class="code" href="namespacearmnn.xhtml#a2a9ac8ebb69307ad4ec894ffa0523dbf">PermuteTensor</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_cpu_tensor_handle.xhtml">ConstCpuTensorHandle</a>* tensor,</div><div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;                                 <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_permutation_vector.xhtml">PermutationVector</a>&amp; permutationVector,</div><div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;                                 <span class="keywordtype">void</span>* permuteBuffer);</div><div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;</div><div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;<span class="keywordtype">void</span> <a class="code" href="namespacearmnn.xhtml#a3170fdd696155a247ecd81d445c0e2e1">ReshapeWeightsForAcl</a>(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>&amp; weightInfo, <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout);</div><div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;</div><div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> <a class="code" href="namespacearmnn.xhtml#a1e8288eac7e909fdb58b6113d816763a">ConvertWeightTensorInfoFromArmnnToAcl</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>&amp; weightInfo, <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout);</div><div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;</div><div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;<a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> <a class="code" href="namespacearmnn.xhtml#a51e8b95a429e11678ffa8b9fdc88351b">ConvertWeightTensorFromArmnnToAcl</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_cpu_tensor_handle.xhtml">ConstCpuTensorHandle</a>* weightTensor,</div><div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;                                                     <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout,</div><div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;                                                     <span class="keywordtype">void</span>* permuteBuffer);</div><div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;</div><div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;}  <span class="comment">//namespace armnn</span></div><div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a></div><div class="ttdeci">DataLayout</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00049">Types.hpp:49</a></div></div>
+<div class="ttc" id="_tensor_8hpp_xhtml"><div class="ttname"><a href="_tensor_8hpp.xhtml">Tensor.hpp</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_a51e8b95a429e11678ffa8b9fdc88351b"><div class="ttname"><a href="namespacearmnn.xhtml#a51e8b95a429e11678ffa8b9fdc88351b">armnn::ConvertWeightTensorFromArmnnToAcl</a></div><div class="ttdeci">armnn::ConstTensor ConvertWeightTensorFromArmnnToAcl(const ConstCpuTensorHandle *weightTensor, DataLayout dataLayout, void *permuteBuffer)</div><div class="ttdef"><b>Definition:</b> <a href="_workload_utils_8cpp_source.xhtml#l00132">WorkloadUtils.cpp:132</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_a1e8288eac7e909fdb58b6113d816763a"><div class="ttname"><a href="namespacearmnn.xhtml#a1e8288eac7e909fdb58b6113d816763a">armnn::ConvertWeightTensorInfoFromArmnnToAcl</a></div><div class="ttdeci">TensorInfo ConvertWeightTensorInfoFromArmnnToAcl(const TensorInfo &amp;weightInfo, DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_workload_utils_8cpp_source.xhtml#l00109">WorkloadUtils.cpp:109</a></div></div>
+<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00053">Tensor.hpp:53</a></div></div>
+<div class="ttc" id="classarmnn_1_1_i_tensor_handle_xhtml_a30c3e09ce55369b66469443a4ca5ef03"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle.xhtml#a30c3e09ce55369b66469443a4ca5ef03">armnn::ITensorHandle::GetStrides</a></div><div class="ttdeci">virtual TensorShape GetStrides() const =0</div><div class="ttdoc">Get the strides for each dimension ordered from largest to smallest where the smallest value is the s...</div></div>
+<div class="ttc" id="classarmnn_1_1_const_cpu_tensor_handle_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_cpu_tensor_handle.xhtml">armnn::ConstCpuTensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="_cpu_tensor_handle_8hpp_source.xhtml#l00027">CpuTensorHandle.hpp:27</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2020 ARM Limited. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00025">00_introduction.dox:25</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_a44affeeb090c3c6a3062830562672e84"><div class="ttname"><a href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a></div><div class="ttdeci">void IgnoreUnused(Ts &amp;&amp;...)</div><div class="ttdef"><b>Definition:</b> <a href="_ignore_unused_8hpp_source.xhtml#l00014">IgnoreUnused.hpp:14</a></div></div>
+<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00020">Tensor.hpp:20</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_a2a9ac8ebb69307ad4ec894ffa0523dbf"><div class="ttname"><a href="namespacearmnn.xhtml#a2a9ac8ebb69307ad4ec894ffa0523dbf">armnn::PermuteTensor</a></div><div class="ttdeci">armnn::ConstTensor PermuteTensor(const ConstCpuTensorHandle *tensor, const PermutationVector &amp;permutationVector, void *permuteBuffer)</div><div class="ttdef"><b>Definition:</b> <a href="_workload_utils_8cpp_source.xhtml#l00013">WorkloadUtils.cpp:13</a></div></div>
+<div class="ttc" id="_profiling_8hpp_xhtml_a5ccc65e2c464ac05ce311fdae7ede03a"><div class="ttname"><a href="_profiling_8hpp.xhtml#a5ccc65e2c464ac05ce311fdae7ede03a">ARMNN_SCOPED_PROFILING_EVENT</a></div><div class="ttdeci">#define ARMNN_SCOPED_PROFILING_EVENT(backendId, name)</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8hpp_source.xhtml#l00169">Profiling.hpp:169</a></div></div>
+<div class="ttc" id="_permute_8hpp_xhtml"><div class="ttname"><a href="_permute_8hpp.xhtml">Permute.hpp</a></div></div>
+<div class="ttc" id="classarmnn_1_1_i_tensor_handle_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle.xhtml">armnn::ITensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_i_tensor_handle_8hpp_source.xhtml#l00015">ITensorHandle.hpp:15</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">armnn::Compute::Undefined</a></div></div>
+<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00199">Tensor.hpp:199</a></div></div>
+<div class="ttc" id="classarmnn_1_1_i_tensor_handle_xhtml_affd5aae75cad90f472f96cfd25a13f29"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle.xhtml#affd5aae75cad90f472f96cfd25a13f29">armnn::ITensorHandle::GetShape</a></div><div class="ttdeci">virtual TensorShape GetShape() const =0</div><div class="ttdoc">Get the number of elements for each dimension ordered from slowest iterating dimension to fastest ite...</div></div>
+<div class="ttc" id="classarmnn_1_1_permutation_vector_xhtml"><div class="ttname"><a href="classarmnn_1_1_permutation_vector.xhtml">armnn::PermutationVector</a></div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00173">Types.hpp:173</a></div></div>
+<div class="ttc" id="_cpu_tensor_handle_8hpp_xhtml"><div class="ttname"><a href="_cpu_tensor_handle_8hpp.xhtml">CpuTensorHandle.hpp</a></div></div>
+<div class="ttc" id="_half_8hpp_xhtml"><div class="ttname"><a href="_half_8hpp.xhtml">Half.hpp</a></div></div>
+<div class="ttc" id="classarmnn_1_1_i_tensor_handle_xhtml_a9afbc055a017adf1bc38ee137bca6e90"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle.xhtml#a9afbc055a017adf1bc38ee137bca6e90">armnn::ITensorHandle::Map</a></div><div class="ttdeci">virtual const void * Map(bool blocking=true) const =0</div><div class="ttdoc">Map the tensor data for access. </div></div>
+<div class="ttc" id="classarmnn_1_1_i_tensor_handle_xhtml_a563609828050f1b3a7868c23f3365923"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle.xhtml#a563609828050f1b3a7868c23f3365923">armnn::ITensorHandle::Unmap</a></div><div class="ttdeci">virtual void Unmap() const =0</div><div class="ttdoc">Unmap the tensor data. </div></div>
+<div class="ttc" id="namespacearmnn_xhtml_ad69ffa576a596b9eb20ab6a41420c541"><div class="ttname"><a href="namespacearmnn.xhtml#ad69ffa576a596b9eb20ab6a41420c541">armnn::ConvertMaskToACLFormat</a></div><div class="ttdeci">int32_t ConvertMaskToACLFormat(int32_t mask, int32_t numDim)</div><div class="ttdef"><b>Definition:</b> <a href="_workload_utils_8cpp_source.xhtml#l00192">WorkloadUtils.cpp:192</a></div></div>
+<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">armnn::TensorShape::GetNumDimensions</a></div><div class="ttdeci">unsigned int GetNumDimensions() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00043">Tensor.hpp:43</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_a92c91193007aa49f4732d6dba5397f8d"><div class="ttname"><a href="namespacearmnn.xhtml#a92c91193007aa49f4732d6dba5397f8d">armnn::CopyTensorContentsGeneric</a></div><div class="ttdeci">void CopyTensorContentsGeneric(const ITensorHandle *srcTensor, ITensorHandle *dstTensor, CopyFunc copy)</div><div class="ttdef"><b>Definition:</b> <a href="_workload_utils_8hpp_source.xhtml#l00049">WorkloadUtils.hpp:49</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_afb5b53a8b0c01d4f27830bef0f25ca09"><div class="ttname"><a href="namespacearmnn.xhtml#afb5b53a8b0c01d4f27830bef0f25ca09">armnn::GatherTensorHandlePairs</a></div><div class="ttdeci">void GatherTensorHandlePairs(const DescriptorType &amp;descriptor, std::vector&lt; std::pair&lt; SrcTensorHandleType *, DstTensorHandleType *&gt;&gt; &amp;tensorHandlePairs)</div><div class="ttdef"><b>Definition:</b> <a href="_workload_utils_8hpp_source.xhtml#l00192">WorkloadUtils.hpp:192</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_a3170fdd696155a247ecd81d445c0e2e1"><div class="ttname"><a href="namespacearmnn.xhtml#a3170fdd696155a247ecd81d445c0e2e1">armnn::ReshapeWeightsForAcl</a></div><div class="ttdeci">void ReshapeWeightsForAcl(TensorInfo &amp;weightInfo, DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_workload_utils_8cpp_source.xhtml#l00036">WorkloadUtils.cpp:36</a></div></div>
+<div class="ttc" id="_profiling_8hpp_xhtml"><div class="ttname"><a href="_profiling_8hpp.xhtml">Profiling.hpp</a></div></div>
+<div class="ttc" id="include_2armnn_2backends_2_i_tensor_handle_8hpp_xhtml"><div class="ttname"><a href="include_2armnn_2backends_2_i_tensor_handle_8hpp.xhtml">ITensorHandle.hpp</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_abdcd184ed3bd648bb31d385040cafd5d"><div class="ttname"><a href="namespacearmnn.xhtml#abdcd184ed3bd648bb31d385040cafd5d">armnn::MaxNumOfTensorDimensions</a></div><div class="ttdeci">constexpr unsigned int MaxNumOfTensorDimensions</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00018">Types.hpp:18</a></div></div>
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